Mining email inboxes for suggesting actions

ABSTRACT

Embodiments are directed towards automatically learning user behavioral patterns when interacting with messages and based on the learned patterns, suggesting one or more predicted actions that a user might take in response to receiving subsequent message. One or more classifiers are trained and employed to predict one or more actions that a user might take in response to receiving the message. In one embodiment, the one or more predicted actions are provided suggested to the user as an action the user might take on the message. Messages may be rank ordered within a given suggested action based on a confidence level of the prediction.

TECHNICAL FIELD

The present invention relates generally to managing messages, such asemail messages, and, more particularly, but not exclusively toautomatically learning user behavioral patterns when interacting withmessages and suggesting one or more actions that a user might take inresponse to receiving a subsequent message. In one embodiment, receivedmessages are rank ordered for a suggested action.

BACKGROUND

Email messages are a central means of communication between users overthe Internet, partly because a user can maintain the messages over anextended period of time. Therefore, many email applications devote asignificant part of their real estate on a computer display screen tooffer users with various organizational mechanisms. For example, today,some messaging applications allow users to create and use folders,labels, or other various organizational tools. Yet, as of today in spiteof numerous efforts, many people still find it tedious and/orcomplicated to use many of the organizational mechanisms provided tothem. Moreover, even after such organizational mechanisms are applied,it may remain difficult for people to determine what to do with themessages. Thus, it is with respect to these considerations and othersthat the present invention has been made.

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting and non-exhaustive embodiments of the present invention aredescribed with reference to the following drawings. In the drawings,like reference numerals refer to like parts throughout the variousfigures unless otherwise specified.

For a better understanding of the present invention, reference will bemade to the following Detailed Description, which is to be read inassociation with the accompanying drawings, wherein:

FIG. 1 is a system diagram of one embodiment of an environment in whichthe invention may be practiced;

FIG. 2 shows one embodiment of a client device that may be included in asystem implementing the invention;

FIG. 3 shows one embodiment of a network device that may be included ina system implementing the invention;

FIG. 4 illustrates a logical flow generally showing one embodiment of anoverview process for use in determining one or more suggested actions auser might take on a message; and

FIG. 5 illustrates one embodiment of a messaging screen display showingpossible, non-exhaustive examples of one or more actions suggested thata user can take on a message.

DETAILED DESCRIPTION

The present invention now will be described more fully hereinafter withreference to the accompanying drawings, which form a part hereof, andwhich show, by way of illustration, specific embodiments by which theinvention may be practiced. This invention may, however, be embodied inmany different forms and should not be construed as limited to theembodiments set forth herein; rather, these embodiments are provided sothat this disclosure will be thorough and complete, and will fullyconvey the scope of the invention to those skilled in the art. Amongother things, the present invention may be embodied as methods ordevices. Accordingly, the present invention may take the form of anentirely hardware embodiment, an entirely software embodiment or anembodiment combining software and hardware aspects. The followingdetailed description is, therefore, not to be taken in a limiting sense.

Throughout the specification and claims, the following terms take themeanings explicitly associated herein, unless the context clearlydictates otherwise. The phrase “in one embodiment” as used herein doesnot necessarily refer to the same embodiment, though it may.Furthermore, the phrase “in another embodiment” as used herein does notnecessarily refer to a different embodiment, although it may. Thus, asdescribed below, various embodiments of the invention may be readilycombined, without departing from the scope or spirit of the invention.

In addition, as used herein, the term “or” is an inclusive “or”operator, and is equivalent to the term “and/or,” unless the contextclearly dictates otherwise. The term “based on” is not exclusive andallows for being based on additional factors not described, unless thecontext clearly dictates otherwise. In addition, throughout thespecification, the meaning of “a,” “an,” and “the” include pluralreferences. The meaning of “in” includes “in” and “on.”

As used herein, the term “feature” refers to any part of a message,including header information and attachments, as well as eventsassociated with the message. Several features are described in moredetail below. Briefly, however, in one embodiment, some features may beconsidered as being specific to a recipient, a sender, or even acombination of sender-recipient. Features may also be associated with acharacteristic of a message. Non-limiting, non-exhaustive examples ofrecipient features include, activity levels for the recipient; a loginfrequency that might indicate, for example, how many logins a user hasdone on their messaging client during a given time period, such as aday, week, month, or the like; a number of messages received during agiven time period; a number or fraction of messages replied to,forwarded, read, discarded, archived, such as to a special folder;annotated the message for a later action; even taking no action on amessage may be included as a feature. Non-limiting, non-exhaustiveexamples of sender features might include counts for tokens, phrases,symbols, or the like, within a “from” or “subject” such as “reminder,”“foursquare,” “facebook mail,” or the like; information indicating thatthe message is processed “from” filed to, detect a gender of the sender;message domain of the sender; tokens from the message address, such as“no-reply,” or the like. Examples of sender-recipient pair featuresmight include, same last name in the “from” and “to” fields; amount ofoverlap in message addresses; historic information of the messagesexchanged, read, replied to; average reply times; average reply ratios;and the like. Examples of message (characteristic) features may includetokens/words in a subject; tokens/words in a body; time of day a messageis sent; time of day the message is read or otherwise acted upon;number, types, size, and names of attachments; number and targets ofUniform Resource Locators (URLs) or the like within a message; messagelength; key words in the message; number of other recipients in a “To,”or “CC” header; and the like. Other features in addition to or in placeof those listed above may also be used to generate a feature vector foreach message.

As used herein, the term “mining” includes searching, examining,extracting information from, and/or otherwise monitoring, a collectionof messages and actions. Mining may then be employed to generate one ormore predictions about how a user might respond to a given message.

The following briefly describes the embodiments of the invention inorder to provide a basic understanding of some aspects of the invention.This brief description is not intended as an extensive overview. It isnot intended to identify key or critical elements, or to delineate orotherwise narrow the scope. Its purpose is merely to present someconcepts in a simplified form as a prelude to the more detaileddescription that is presented later.

Briefly stated, the present invention is directed towards automaticallylearning user behavioral patterns when interacting with messages andbased on the learned patterns, suggesting one or more actions that auser might take in response to receiving a subsequent message. In oneembodiment, a plurality of features, are extracted from a plurality ofmessages, as well as from events or actions associated with themessages, to generate a plurality of feature vectors. Variousclassifiers are then trained, including horizontal classifiers andvertical classifiers, using the feature vectors. Briefly, a horizontalclassifier may include virtually any classifier that is trained across aplurality of users' inboxes, and actions upon the messages to determinea “wisdom of the crowds,” suggested action. Vertical classifiers mayinclude virtually any classifier that is trained on a single user'sinbox and actions upon messages. In one embodiment, multiple verticalclassifiers may be employed, including a vertical general classifierthat is trained based on a particular user, and another verticalpair-wise classifier that is trained based on a particular recipient(user)-sender pair relationship for messages. In one embodiment, theclassifiers may be binary classifiers that are configured to take afeature vector of an incoming message and to output a binary decision,such as a yes/no, for a given action. Other classifiers may also beemployed, including a time regression classifier that provides, forexample, a response to what is an expected time until a certain actionwill be taken, or a similar output.

Then, for each new incoming message, a feature vector may be generatedand one or more of the above classifiers are employed to produce a setof one or more predicted actions that a user might take on the incomingmessage. In one embodiment, the results of the one or more classifiersmay be combined to provide a weighted suggested action. In oneembodiment, the classifiers may further provide a confidence valueindicating a level of confidence in the output predicted action to betaken. The confidence value may then be employed, in one embodiment, torank order messages within a given predicted action. In still anotherembodiment, actions might be rank ordered based on a variety of metrics,including, but not limited to a quantity of messages, a collectiveconfidence value for the messages with each action, or the like. Themessages may then be displayed within a messaging client to the user,along with the predicted actions, where the predicted actions may beconsidered as actions suggested to the user to take on a given message.In one embodiment, more than one action may be suggested to be taken fora message. In one embodiment, the multiple actions for a message may belogically arranged, such as “read,” then, “reply.” However, otherordering criteria may also be employed. In one embodiment, the displayedsuggested actions may include a selectable icon that when selected bythe user initiates the suggested action.

Providing explicit suggested actions to be performed on a message isdirected in part to providing actions that are intended to be of asimilar nature as actions that are actually observed, either globallyover a plurality of users, and/or for a particular user. Such suggestedactions may also enable improved social interactions, as it mayencourage and assist users in focusing their attention on more relevantsocial relationships. Further, providing suggested actions is directedalso to providing a more informative mechanism of guidance to the userover other mechanisms that, for example, merely indicate whether amessage is important or not. In addition, providing predicted actions assuggested actions that a user might take on a message are also directedtowards enabling conversations to be preserved between the user andothers.

It should also be recognized that while the disclosure is described interms of email messages, embodiments are not so limited. Thus, in otherembodiments, other types of messages for which a user may maintain overa period of time may also be classified using suggested actions.Moreover, it should be recognized that other types of content may alsoemploy the embodiments, including, without limit to organizing, musiccontent, video content, audio content, documents, or the like, based inpart on a suggested action to be taken by a user.

It should also be recognized that while messages are disclosed herein,other applications may also employ the various embodiments, to enhancesharing of advertisements, and/or other items, usable to monetize asuggested action. For example, in one embodiment, based on predictionsof how a particular user might respond to a given advertisement, one ormore advertisements might be sent to the particular user. In thismanner, for example, a user that is predicted to respond to particularadvertisements might be provided those advertisements. Similarly, if agiven user is predicted to more likely to forward particularadvertisements, those advertisements might be directed to those users.In this way, directed and focused advertisements may be provided.

Illustrative Operating Environment

FIG. 1 shows components of one embodiment of an environment in which theinvention may be practiced. Not all the components may be required topractice various embodiments, and variations in the arrangement and typeof the components may be made. As shown, system 100 of FIG. 1 includeslocal area networks (“LANs”)/wide area networks (“WANs”)-(network) 111,wireless network 110, client devices 101-105, and Message Action Tagger(MAT) 107.

One embodiment of client devices 101-105 is described in more detailbelow in conjunction with FIG. 2. Generally, however, client devices102-104 may include virtually any portable computing device capable ofreceiving and sending a message over a network, such as network 111,wireless network 110, or the like. Client devices 102-104 may also bedescribed generally as client devices that are configured to beportable. Thus, client devices 102-104 may include virtually anyportable computing device capable of connecting to another computingdevice and receiving information. Such devices include portable devicessuch as, cellular telephones, smart phones, display pagers, radiofrequency (RF) devices, infrared (IR) devices, Personal DigitalAssistants (PDAs), handheld computers, laptop computers, wearablecomputers, tablet computers, integrated devices combining one or more ofthe preceding devices, and the like. As such, client devices 102-104typically range widely in terms of capabilities and features. Forexample, a cell phone may have a numeric keypad and a few lines ofmonochrome Liquid Crystal Display (LCD) on which only text may bedisplayed. In another example, a web enabled mobile device may have atouch sensitive screen, a stylus, and several lines of color LCD inwhich both text and graphics may be displayed.

Client device 101 may include virtually any computing device capable ofcommunicating over a network to send and receive information, includingmessaging, performing various online actions, or the like. The set ofsuch devices may include devices that typically connect using a wired orwireless communications medium such as personal computers,multiprocessor systems, microprocessor-based or programmable consumerelectronics, network Personal Computers (PCs), or the like. In oneembodiment at least some of client devices 102-104 may operate overwired and/or wireless network. Client device 105 may include virtuallyany device useable as a television device. Today, many of these devicesinclude a capability to access and/or otherwise communicate over anetwork such as network 111 and/or even wireless network 110. Moreover,client device 105 may access various computing applications, including abrowser, or other web-based application.

A web-enabled client device may include a browser application that isconfigured to receive and to send web pages, web-based messages, and thelike. The browser application may be configured to receive and displaygraphics, text, multimedia, and the like, employing virtually anyweb-based language, including a wireless application protocol messages(WAP), and the like. In one embodiment, the browser application isenabled to employ Handheld Device Markup Language (HDML), WirelessMarkup Language (WML), WMLScript, JavaScript, Standard GeneralizedMarkup Language (SGML), HyperText Markup Language (HTML), eXtensibleMarkup Language (XML), HTML5, and the like, to display and send amessage. In one embodiment, a user of the client device may employ thebrowser application to perform various actions over a network (online).For example, the user of the client device may select to access andmanage a user message account, send messages, organize messages, createuser folders or the like. However, another application may also be usedto perform various online actions.

For example, client devices 101-105 also may include at least one otherclient application that is configured to access and/or manage usermessage accounts, between another computing device. The clientapplication may include a capability to provide and receive textualcontent, graphical content, audio content, and the like. The clientapplication may further provide information that identifies itself,including a type, capability, name, and the like. In one embodiment,client devices 101-105 may uniquely identify themselves through any of avariety of mechanisms, including a phone number, Mobile IdentificationNumber (MIN), an electronic serial number (ESN), or other mobile deviceidentifier. The information may also indicate a content format that themobile device is enabled to employ. Such information may be provided ina network packet, or the like, sent between other client devices, MATServices 107, or other computing devices.

Client devices 101-105 may further be configured to include a clientapplication that enables an end-user to log into a user message accountthat may be managed by another computing device, such as MAT Services107 or the like. Such user message account, for example, may beconfigured to enable the user to manage one or more online actions,including for example, compose messages, delete messages, replay tomessages, forward messages, archive messages, create folders, movemessages to folders, or the like.

Wireless network 110 is configured to couple client devices 102-104 andits components with network 111. Wireless network 110 may include any ofa variety of wireless sub-networks that may further overlay stand-alonead-hoc networks, and the like, to provide an infrastructure-orientedconnection for client devices 102-104. Such sub-networks may includemesh networks, Wireless LAN (WLAN) networks, cellular networks, and thelike.

Wireless network 110 may further include an autonomous system ofterminals, gateways, routers, and the like connected by wireless radiolinks, and the like. These connectors may be configured to move freelyand randomly and organize themselves arbitrarily, such that the topologyof wireless network 110 may change rapidly.

Wireless network 110 may further employ a plurality of accesstechnologies including 2nd (2G), 3rd (3G), 4th (4G), 5th (5G) generationradio access for cellular systems, WLAN, Wireless Router (WR) mesh, andthe like. Access technologies such as 2G, 3G, 4G, and future accessnetworks may enable wide area coverage for mobile devices, such asclient devices 102-104 with various degrees of mobility. For example,wireless network 110 may enable a radio connection through a radionetwork access such as Global System for Mobil communication (GSM),General Packet Radio Services (GPRS), Enhanced Data GSM Environment(EDGE), Wideband Code Division Multiple Access (WCDMA), and the like. Inessence, wireless network 110 may include virtually any wirelesscommunication mechanism by which information may travel between clientdevices 102-104 and another computing device, network, and the like.

Network 111 is configured to couple network devices with other computingdevices, including, MAT Services 107, client devices 101 and 105, andthrough wireless network 110 to client devices 102-104. Network 111 isenabled to employ any form of computer readable media for communicatinginformation from one electronic device to another. Also, network 111 caninclude the Internet in addition to local area networks (LANs), widearea networks (WANs), direct connections, such as through a universalserial bus (USB) port, other forms of computer-readable media, or anycombination thereof. On an interconnected set of LANs, including thosebased on differing architectures and protocols, a router acts as a linkbetween LANs, enabling messages to be sent from one to another. Inaddition, communication links within LANs typically include twisted wirepair or coaxial cable, while communication links between networks mayutilize analog telephone lines, full or fractional dedicated digitallines including T1, T2, T3, and T4, Integrated Services Digital Networks(ISDNs), Digital Subscriber Lines (DSLs), wireless links includingsatellite links, or other communications links known to those skilled inthe art. For example, various Internet Protocols (IP), Open SystemsInterconnection (OSI) architectures, and/or other communicationprotocols, architectures, models, and/or standards, may also be employedwithin network 111 and wireless network 110. Furthermore, remotecomputers and other related electronic devices could be remotelyconnected to either LANs or WANs via a modem and temporary telephonelink. In essence, network 111 includes any communication method by whichinformation may travel between computing devices.

Additionally, communication media typically embodies computer-readableinstructions, data structures, program modules, or other transportmechanism and includes any information delivery media. By way ofexample, communication media includes wired media such as twisted pair,coaxial cable, fiber optics, wave guides, and other wired media andwireless media such as acoustic, RF, infrared, and other wireless media.Such communication media is distinct from, however, computer-readabledevices described in more detail below.

MAT Services 107 may include virtually any network device usable tooperate as a messaging service to provide messages and suggested actionsfor the messages to client devices 101-105. Such messages may include,but is not limited to email, instant messages, and the like. Oneembodiment of MAT Services 107 is described in more detail below inconjunction with FIG. 3, Briefly, however, MAT Services 107 representsone or more network devices that may monitor a plurality of user actionsupon a set of messages to automatically learn user behavioral patternswhen interacting with messages. In one embodiment, one or more machinelearning classifiers may be trained on the set of messages to learn theusers' behavioral patterns. Then, based on the learned patterns, MATServices 107 may suggest one or more actions that a user might take inresponse to receiving subsequent messages. MAT Services 107 may providea display of the suggested actions within a messaging client to enable auser to interact and select the one or more suggested actions. MATServices 107 may further monitor subsequent actions actually taken bythe users to revise and/or retrain its classifiers. MAT Services 107 mayemploy a process such as that which is described below in conjunctionwith FIG. 4 to perform at least some of its actions. Further, in oneembodiment, MAT Services 107 may provide a display to a user, such asdescribed further below in conjunction with FIG. 5.

Devices that may operate as MAT Services 107 include various networkdevices, including, but not limited to personal computers, desktopcomputers, multiprocessor systems, microprocessor-based or programmableconsumer electronics, network PCs, server devices, network appliances,and the like. It should be noted that while MAT Services 107 isillustrated as a single network device, the invention is not so limited.Thus, in another embodiment, MAT Services 107 may represent a pluralityof network devices. For example, in one embodiment, MAT Services 107 maybe implemented using a cloud architecture, being distributed over aplurality of network devices.

Moreover, MAT Services 107 is not limited to a particular configuration,Thus, MAT Services 107 may operate using a master/slave approach over aplurality of network devices, within a cluster architecture, apeer-to-peer architecture, and/or any of a variety of otherarchitectures. Thus, MAT Services 107 is not to be construed as beinglimited to a single environment, and other configurations, andarchitectures are also envisaged.

Illustrative Client Device

FIG. 2 shows one embodiment of client device 200 that may be included ina system implementing the invention. Client device 200 may include manymore or less components than those shown in FIG. 2. However, thecomponents shown are sufficient to disclose an illustrative embodimentfor practicing the present invention. Client device 200 may represent,for example, one embodiment of at least one of client devices 101-105 ofFIG. 1.

As shown in the figure, client device 200 includes a processing unit(CPU) 222 in communication with a mass memory 230 via a bus 224. Clientdevice 200 also includes a power supply 226, one or more networkinterfaces 250, an audio interface 252, a display 254, a keypad 256, anilluminator 258, an input/output interface 260, a haptic interface 262,and an optional global positioning systems (GPS) receiver 264. Powersupply 226 provides power to client device 200. A rechargeable ornon-rechargeable battery may be used to provide power. The power mayalso be provided by an external power source, such as an AC adapter or apowered docking cradle that supplements and/or recharges a battery. Inone embodiment, although not shown, a gyroscope may be employed inclient device 200 to measure and/or maintain an orientation of clientdevice 200, and/or an orientation of a displayed image.

Client device 200 may optionally communicate with a base station (notshown), or directly with another computing device. Network interface 250includes circuitry for coupling client device 200 to one or morenetworks, and is constructed for use with one or more communicationprotocols and technologies including, but not limited to, global systemfor mobile communication (GSM), code division multiple access (CDMA),time division multiple access (TDMA), user datagram protocol (UDP),transmission control protocol/Internet protocol (TCP/IP), Short MessageService (SMS), general packet radio service (CPRS), WAP, ultra wide band(UWB), IEEE 802.16 Worldwide Interoperability for Microwave Access(WiMax), Session Initiation Protocol/Real-time Transport Protocol(SIP/RTP), or any of a variety of other wireless communicationprotocols. Network interface 250 is sometimes known as a transceiver,transceiving device, or network interface card (NIC).

Audio interface 252 is arranged to produce and receive audio signalssuch as the sound of a human voice. For example, audio interface 252 maybe coupled to a speaker and microphone (not shown) to enabletelecommunication with others and/or generate an audio acknowledgementfor some action. Display 254 may be a liquid crystal display (LCD), gasplasma, light emitting diode (LED), or any other type of display usedwith a computing device. Display 254 may also include a touch sensitivescreen arranged to receive input from an object such as a stylus or adigit from a human hand. In one embodiment, video interface 259 isconfigured to enable any of a variety of input/outputs for video digitaldata over a network.

Keypad 256 may comprise any input device arranged to receive input froma user. For example, keypad 256 may include a push button numeric dial,or a keyboard. Keypad 256 may also include command buttons that areassociated with selecting and sending images. Illuminator 258 mayprovide a status indication and/or provide light. Illuminator 258 mayremain active for specific periods of time or in response to events. Forexample, when illuminator 258 is active, it may backlight the buttons onkeypad 256 and stay on while the client device is powered. Also,illuminator 258 may backlight these buttons in various patterns whenparticular actions are performed, such as dialing another client device.Illuminator 258 may also cause light sources positioned within atransparent or translucent case of the client device to illuminate inresponse to actions.

Client device 200 also comprises input/output interface 260 forcommunicating with external devices, such as a headset, or other inputor output devices not shown in FIG. 2. Input/output interface 260 canutilize one or more communication technologies, such as USB, infrared,Bluetooth™, or the like. Haptic interface 262 is arranged to providetactile feedback to a user of the client device. For example, the hapticinterface may be employed to vibrate client device 200 in a particularway when another user of a computing device is calling.

Optional GPS transceiver 264 can determine the physical coordinates ofclient device 200 on the surface of the Earth, which typically outputs alocation as latitude and longitude values. GPS transceiver 264 can alsoemploy other geo-positioning mechanisms, including, but not limited to,triangulation, assisted GPS (AGPS), Enhanced Observed Time Difference(E-OTD), Cell Identifier (CI), Service Area Identifier (SAI), EnhancedTiming Advance (ETA), Base Station Subsystem (BSS), or the like, tofurther determine the physical location of client device 200 on thesurface of the Earth. It is understood that under different conditions,UPS transceiver 264 can determine a physical location within millimetersfor client device 200; and in other cases, the determined physicallocation may be less precise, such as within a meter or significantlygreater distances. In one embodiment, however, mobile device may throughother components, provide other information that may be employed todetermine a physical location of the device, including for example, aMedia Access Control (MAC) address, IP address, or the like.

Mass memory 230 includes a Random Access Memory (RAM) 232, a Read-OnlyMemory (ROM) 234, and other storage means. Mass memory 230 illustratesan example of computer readable storage media (devices) for storage ofinformation such as computer readable instructions, data structures,program modules or other data. Mass memory 230 stores a basicinput/output system (“BIOS”) 240 for controlling low-level operation ofclient device 200, The mass memory also stores an operating system 241for controlling the operation of client device 200. It will beappreciated that this component may include a general-purpose operatingsystem such as a version of UNIX, or LINUX™, or a specialized clientcommunication operating system such as Windows Mobile™, or the Symbian®operating system. The operating system may include, or interface with aJava virtual machine module that enables control of hardware componentsand/or operating system operations via Java application programs.

Memory 230 further includes one or more data storage 248, which can beutilized by client device 200 to store, among other things, applications242 and/or other data. For example, data storage 248 may also beemployed to store information that describes various capabilities ofclient device 200. The information may then be provided to anotherdevice based on any of a variety of events, including being sent as partof a header during a communication, sent upon request, or the like. Datastorage 248 may also be employed to store folders, address books, buddylists, aliases, user profile information, multimedia content, or thelike. Data storage 248 may also be configured to store messages, messagefolders, information about suggested actions, and/or other informationrelated to managing of messages. Further, as illustrated, data storage248 may also store web page content, or any of a variety of usergenerated content. In one embodiment, a user may download, and/orotherwise access for storage in data storage 248 one or more foldersuseable for organizing messages. At least a portion of the informationmay also be stored on a disk drive or other computer-readable storagedevice (not shown) within client device 200.

Applications 242 may include computer executable instructions which,when executed by client device 200, transmit, receive, and/or otherwiseprocess messages (e.g., SMS, Multimedia Message Service (MMS), InstantMessage (IM), email, and/or other messages), audio, video, and enabletelecommunication with another user of another client device. Otherexamples of application programs include calendars, search programs,email clients, IM applications, SMS applications, Voice Over InternetProtocol (VOID) applications, contact managers, task managers,transcoders, database programs, word processing programs, securityapplications, spreadsheet programs, games, search programs, and soforth. Applications 242 may include, for example, messaging 243 andbrowser 245.

Browser 245 may include virtually any application configured to receiveand display graphics, text, multimedia, and the like, employingvirtually any web based language. In one embodiment, the browserapplication is enabled to employ Handheld Device Markup Language (HDML),Wireless Markup Language (WML), WMLScript, JavaScript, StandardGeneralized Markup Language (SMGL), HyperText Markup Language (HTML),eXtensible Markup Language (XML), and the like, to display and send amessage. However, any of a variety of other web-based languages may beemployed. In one embodiment, browser 245 may enable a user of clientdevice 200 to access/or otherwise manage a user message account, such asYahoo! Mail, Hotmail, Gmail, or the like.

Messaging 243 may be configured to manage a user message account usingany of a variety of messaging communications including, but not limitedto email, Short Message Service (SMS), Instant Message (IM), MultimediaMessage Service (MMS), internet relay chat (WC), mIRC, RSS feeds, and/orthe like. For example, in one embodiment, messaging 243 may beconfigured as a mail user agent (MUA) such as Elm, Pine, MessageHandling (MH), Outlook, Eudora, Mac Mail, Mozilla Thunderbird, or thelike. In another embodiment, messaging 243 may be a client applicationthat is configured to integrate and employ a variety of messagingprotocols, including, but not limited to various push and/or pullmechanisms for client device 200. In one embodiment, messaging 243 mayinteract with browser 245 for managing messages. As used herein, theterm “message” refers to any of a variety of messaging formats, orcommunications forms, including but not limited to email, SMS, IM, MMS,IRC, or the like. A user may employ messaging 243 to access one or moremessages and perform various actions upon the messages, including, butnot limited to moving the messages from one folder to another folder;deleting a message; forwarding a message, responding to a message;tagging, labeling, or otherwise providing an identifier to a message. Inone embodiment, the identifier may then be employed to sort and/orotherwise organize the messages. In one embodiment, the identifier mightbe associated with a suggested action that a user might take upon amessage, the suggested action being automatically generated withoutadditional user actions upon the message with which the suggested actionis associated. Such suggested actions may be generated by one or moreremote applications, or by one or more applications that might residewithin client device 200.

Illustrative Network Device

FIG. 3 shows one embodiment of a network device 300, according to oneembodiment of the invention. Network device 300 may include many more orless components than those shown. The components shown, however, aresufficient to disclose an illustrative embodiment for practicing theinvention. Network device 300 may represent, for example, MAT Services107 of FIG. 1.

Network device 300 includes processing unit 312, video display adapter314, and a mass memory, all in communication with each other via bus322. The mass memory generally includes RAM 316, ROM 332, and one ormore permanent mass storage devices, such as hard disk drive 328, tapedrive, optical drive, flash drive, and/or floppy disk drive. The massmemory stores operating system 320 for controlling the operation ofnetwork device 300. Any general-purpose operating system may beemployed. Basic input/output system (“BIOS”) 318 is also provided forcontrolling the low-level operation of network device 300. Asillustrated in FIG. 3, network device 300 also can communicate with theInternet, or some other communications network, via network interfaceunit 310, which is constructed for use with various communicationprotocols including the TCP/IP protocol. Network interface unit 310 issometimes known as a transceiver, transceiving device, or networkinterface card (NIC). Network device 300 also includes input/outputinterface 324 for communicating with external devices, such as aheadset, or other input or output devices not shown in FIG. 3.Input/output interface 324 can utilize one or more communicationtechnologies, such as USB, infrared, Bluetooth™, or the like.

The mass memory as described above illustrates another type ofcomputer-readable media, namely computer-readable storage media.Computer-readable storage media (devices) may include volatile,nonvolatile, removable, and non-removable media implemented in anymethod or technology for storage of information, such as computerreadable instructions, data structures, program modules, or other data.Examples of computer readable storage media include RAM, ROM,Electronically Erasable Programmable Read-Only Memory (EEPROM), flashmemory or other memory technology, Compact Disc Read-Only Memory(CD-ROM), digital versatile disks (DVD) or other optical storage,magnetic cassettes, magnetic tape, magnetic disk storage or othermagnetic storage devices, or any other physical medium which can be usedto store the desired information and which can be accessed by acomputing device.

As shown, data stores 354 may include a database, text, spreadsheet,folder, file, or the like, that may be configured to maintain and storeuser account identifiers, user profiles, email addresses, IM addresses,and/or other network addresses; or the like. Data stores 354 may alsostore various authoritative scores, citation models, and the like. Datastores 354 may further include program code, data, algorithms, and thelike, for use by a processor, such as central processing unit (CPU) 312to execute and perform actions. In one embodiment, at least some of dataand/or instructions stored in data stores 354 might also be stored onanother device of network device 300, including, but not limited tocd-rom/dvd-rom 326, hard disk drive 328, or other computer-readablestorage device resident on network device 300 or accessible by networkdevice 300 over, for example, network interface unit 310.

The mass memory also stores program code and data. One or moreapplications 350 are loaded into mass memory and run on operating system320. Examples of application programs may include transcoders,schedulers, calendars, database programs, word processing programs,Hypertext Transfer Protocol (HTTP) programs, customizable user interfaceprograms, IPSec applications, encryption programs, security programs,SMS message servers, IM message servers, email servers, accountmanagers, and so forth. Web services 356, messaging server 358, andMessage Action Suggester (MAS) 357, may also be included as applicationprograms within applications 350. MAS 357 may also be stored ascomputer-executable instructions in a computer-readable storage devicesuch as those described above, such that when the computer-readablestorage device is installed into a computing device, such as networkdevice 300, or the like, CPU 312 may then execute thecomputer-executable instructions to perform various actions includingthose disclosed herein for MAS 357.

MAS 357 is configured to monitor a plurality of user actions upon a setof messages to automatically learn user behavioral patterns when theusers are interacting with the messages. MAS 357 may train one or moremachine learning classifiers on the set of messages to learn the users'behavioral patterns. Based on the learned patterns, MAS 357 may suggestone or more actions that a user might take in response to receivingsubsequent messages. The suggested actions may include any of a varietyof actions that a user might take upon a received message, including,but not limited to reading the message, replying to the message,forwarding the message, deleting the message, archiving the message,such as moving the message to a special folder, or even indicating thatno action is suggested to be taken for the message. Other actions mayalso be suggested, thus, the above examples are not to be construed asexhaustive or otherwise limiting. Moreover, MAS 357 may provide aplurality of suggested actions to be taken upon a given message.

As noted, MAS 357 may train a plurality of classifiers, including, forexample, a horizontal classifier based on a plurality of message users.Such horizontal classifier is directed towards predicting how usersmight behave in general. The horizontal classifier might be configuredto determine a variety of actions. Non-exhaustive, non-limiting exampleinclude, how do users generally reply to subjects containing ‘jokes’; dousers generally read messages from users they have sent many messages toin the past; do users generally reply to messages from a particulardomain; do users generally reply to messages sent by others with thesame last name as the user; or even do users generally forward messagessent by others for whom the user has a fax number, phone number, orother information about the other user in their address book or thelike? These are clearly merely possible question sets associated withhorizontal classifications.

Another classifier may include a vertical general classifier that isdirected towards looking at a particular message recipient, while athird vertical pair-wise classifier might examine particular recipientsender pairs. Vertical general classifiers might include examining suchnon-limiting, non-exhaustive questions such as: does this user generallyreply to subjecting containing a particular word, such as ‘ fun’; doesthis user generally read messages from users the user has sent manymessage to in the past; does this user generally read messages receivedwhere the user is on a Cc list; does this user generally reply tomessages sent by a particular gender; or even does this user generallyread messages by close friends, such as those identified as such intheir address book, or any of a variety of other questions.

Similarly, vertical pair-wise classifiers might include examining suchnon-limiting, non-exhaustive questions such as: does this user generallyread messages from a particular user; or even does this user reply tosubject ‘jokes’ sent by a particular user; or the like. Clearly, theabove are merely examples. Moreover, labels such as ‘family,’ ‘closefriend,’ or the like are merely illustrative and are not intended tonarrow the scope of an embodiment. Further, such classifiers may findgroupings based on a variety of other meanings, questions, or the like.

In any event, MAS 357 may further obtain from a plurality of messages aset of training feature vectors that may include a set of labelsindicating an action, such as “was read,” “was replied to,” and similaraction related labels. MAS 357 may then employ the training featurevectors to train the one or more classifiers to be directed towardsmapping new, unseen feature vectors to one or more action labels. MAS357 may employ a variety of features, including, but not limited tothose described above to generate feature vectors.

MAS 357 may then employ a combination of one or more classifiers togenerate a predicted action that a particular user might take for agiven received message. In one embodiment MAS 357 may further obtainfrom the one or more classifiers a value that indicates a confidencelevel of the classifier in its prediction. Such confidence levels maythen be combined to provide a ranking for a message for a predictedaction. In one embodiment, the ranking may be used to rank order themessages within a predicted action, the predicted action being displayedwith the message, as a suggested action that the user might take on agiven message. Moreover, the confidence levels, a number of messages ina given action, or a variety of other metrics may be used to rank orderactions across the messages, and/or even rank order a plurality ofactions for a given message. In any event, MAS 357 may display resultsof the rank ordered messages and/or actions within a display for aclient device, using for example, a screen display such as describedbelow in conjunction with FIG. 5. Further MAS 357 may employ a processsuch as disclosed below in conjunction with FIG. 4 to perform at leastsome of its actions.

Web services 356 represent any of a variety of services that areconfigured to provide content, including messages, over a network toanother computing device. Thus, web services 356 include for example, aweb server, a File Transfer Protocol (FTP) server, a database server, acontent server, or the like. Web services 356 may provide the contentincluding messages over the network using any of a variety of formats,including, but not limited to WAP, HDML, WML, SGML, HTML, XML, compactHTML (cHTML), extensible (xHTML), or the like.

In one embodiment, Web services 356 may receive content, includingmessages from another network device, such as a client device, or thelike. Web services 356 may then enable a user to manage a user messageaccount. As such, web services 356 may allow users to compose messages,delete messages, move messages to folders, create folders, or the like.

In one embodiment, Web services 356 (and/or messaging 358) may interactwith MAS 357 to automatically display suggested actions that a usermight take upon a message. In one embodiment, messages may be rankordered within a given action to indicate a priority for taking thesuggested action on a message. In one embodiment, selecting an icon nextto the message that indicates the suggested action may initiate thesuggested action. Thus, for example, in one embodiment, selecting anicon next to a message where the icon indicates that the message is tobe ‘forwarded’ might result in the message being configured in a displayscreen at a client device ready to be forwarded. In one embodiment, asuggested list of recipients might also be provided to the user. Theuser may then edit the suggested list of recipients by adding and/ordeleting one or more recipients in the list. In addition, the messagemay be further configured with an appropriate section added within thebody ready for additional information to be entered by the user.However, in other embodiments, other portions of the message might bemodified, including, pre-inserting the user's signature block, and/orother edits to the received message might also be suggested.

Generalized Operation

The operation of certain aspects of the invention will now be describedwith respect to FIG. 4. The operations described below for FIG. 4 may,in one embodiment, be performed within one or more network devices, suchas MAT Services 107 of FIG. 1.

Process 400 of FIG. 4 begins after a start block, at block 402, whereactions of a plurality of users are monitored over a plurality ofmessages to generate an initial training set of feature vectors andactions performed by the users on the messages. In one embodiment, thistraining set of feature vectors and labels of actions taken may beobtained using any of a variety of mechanisms.

Processing then flows to block 404 where a horizontal classifier istrained using the feature vectors and associated actions. Moving toblocks 406 and 408 vertical classifiers are also trained for each of aplurality of users, to generate classifiers that are specific to a givenuser (vertical general classifier) and to a given user-sender pair(vertical pair-wise classifier).

Continuing next to block 410, the trained classifiers may then beemployed to predict actions that a given user might take for a givenmessage. Therefore, at block 410, a message is received for a user.Moving to block 412, a feature vector is generated for the receivedmessage, based on the discussions above.

Flowing next to decision block 414, a determination is made whether theuser is determined to be a new user. That is, in one embodiment, adetermination is made as to whether a history of actions have beenmonitored and employed to train vertical classifiers for this user. Ifthe user is not new, then processing branches to decision block 416;otherwise, processing branches to block 422.

At decision block 416, a determination is made whether the sender of themessage is new to the user. That is, has this user received and actedupon messages from this sender in the past, such that a verticalclassifier has been trained based on this sender-user pair? If thissender is not new to this user, processing flows to block 418;otherwise, processing continues to block 420.

At block 418, the vertical pair-wise classifier for this sender-userpair is employed to predict an action that this user is likely to takeon this message given previous information about actions this user hastaken given this message sender. In one embodiment, the classifier mayalso generate a confidence level indicating a level of confidence thatthe classifier provides for its predicted action. In one embodiment, aplurality of actions may be predicted. Processing continues next toblock 420.

At block 420, the vertical general classifier for this user is employedto predict an action that this user is likely to take on this messagebased on previous information about actions this user has generallytaken on messages having similar feature vectors. In one embodiment, theclassifier may also generate a confidence level indicating a level ofconfidence that the classifier provides for its predicted action. In oneembodiment, a plurality of actions may be predicted. Processingcontinues next to block 422.

At block 422, the horizontal general classifier is employed to predictan action that is likely to be taken on this message based on previousinformation about actions generally taken on messages having similarfeature vectors by a plurality of users. In one embodiment, theclassifier may also generate a confidence level indicating a level ofconfidence that the classifier provides for its predicted action. In oneembodiment, a plurality of actions may be predicted. Processingcontinues next to block 424.

At block 424, the predictions from one or more of the classifiers may becombined. In one embodiment, a weighted average of the predictions maybe used to generate the predicted action(s). In one embodiment,weighting coefficients for the combining of the predictions may be basedon a size of a user's history. Thus, for example, where there isdetermined to be a statistically significant sample size of actions forthe user-sender pair, results from the vertical pair-wise classifiermight be weighted higher than the predictions from the otherclassifiers. In another embodiment, where each at least one classifierpredicts a statistically significant action that is different from anaction predicted by the other classifiers, each action determined to bestatistically significant may be retained for display. Statisticallysignificant results may be based on a variety of statistical analysiscriteria, including, sample size, desired levels for Type I errors, TypeII errors, and the like. Thus, statistically significant values may bedetermined based on engineering judgment, desired confidence levelsabove a threshold, and the like. In any event, one or more predictedactions may be determined for a given message, along with associatedconfidence levels for each of the predicted actions.

Processing then flows to block 426, where the message is tagged orotherwise labeled or identified with its predicted action(s). In oneembodiment, for a given predicted action, messages, including themessage, may be rank ordered for display. In one embodiment, themessages may be rank ordered based on the confidence level determinedfor the message for the given action. Where a message has multiplepredicted actions, these actions may be ordered for that message basedon confidence levels. It should be noted that while confidence levelsfrom the classifiers are disclosed as being used to rank order actions,and/or messages within an action, other metrics may also be employed inother embodiments. Further, at block 426, the message(s) along withpredicted actions are displayed to the user, where such predictedactions are provided as suggested actions that the user is suggested totake on a given message.

Processing next flows to block 428, where the user may take any of aplurality of actions, including, but not limited to the suggestedactions. Further, as described elsewhere, selection of various displayedaction icons enables the user to readily perform the suggested action,including, in at least one embodiment, taking suggested actions that aredirected towards preserving a conversation associated with a message,message thread, or the like. Actions actually taken by the user on themessage, and/or other messages are monitored, and may then be useable toretrain one or more of the classifiers. Thus, although not explicitlyillustrated, it should be understood that blocks 402, 404, 406, and 408may be performed virtually anytime based on feedback from one or moreusers, monitored actions of the users, and the like. In this manner, asize of history of a given user may be modified.

Processing then flows decision block 430, where a determination is madewhether to continue to receive messages for a given user, and to predictone or more actions to suggest that the user take on the receivedmessages. If so, processing may loop back to block 410 or 402 forretraining, Otherwise, process 400 may return to a calling process toperform other actions.

It will be understood that each block of the flowchart illustration, andcombinations of blocks in the flowchart illustration, can be implementedby computer program instructions. These program instructions may beprovided to a processor to produce a machine, such that theinstructions, which execute on the processor, create means forimplementing the actions specified in the flowchart block or blocks. Thecomputer program instructions may be executed by a processor to cause aseries of operational steps to be performed by the processor to producea computer-implemented process such that the instructions, which executeon the processor to provide steps for implementing the actions specifiedin the flowchart block or blocks. The computer program instructions mayalso cause at least some of the operational steps shown in the blocks ofthe flowchart to be performed in parallel. Moreover, some of the stepsmay also be performed across more than one processor, such as mightarise in a multi-processor computer system. In addition, one or moreblocks or combinations of blocks in the flowchart illustration may alsobe performed concurrently with other blocks or combinations of blocks,or even in a different sequence than illustrated without departing fromthe scope or spirit of the invention.

Accordingly, blocks of the flowchart illustration support combinationsof means for performing the specified actions, combinations of steps forperforming the specified actions and program instruction means forperforming the specified actions. It will also be understood that eachblock of the flowchart illustration, and combinations of blocks in theflowchart illustration, can be implemented by special purposehardware-based systems, which perform the specified actions or steps, orcombinations of special purpose hardware and computer instructions.

Illustrative Display

FIG. 5 illustrates one embodiment of a messaging screen display showingpossible, non-exhaustive examples of one or more actions suggested thata user can take on a message. Screen 500 may be managed using processessuch as described above for display at a client device, such as clientdevices 101-105 of FIG. 1. Not all the components illustrated in screen500 may be required to practice various embodiments, and variations inthe arrangement and type of the components may be made. As shown, screen500 of FIG. 5 includes a plurality of messages 501. Such plurality ofmessages 501 may be displayed with a variety of information associatedwith the message; however, such information is not to be construed aslimiting, and other information about the messages may also bedisplayed. Thus, as shown, for the plurality of messages 501, aresubject information, tags, dates, and from (sender information). Alsoillustrated for the plurality of messages 501 are one or more actions502 for each of the plurality of messages 501. For example, asillustrated for message 506, a suggested action 503 indicates that theuser might ‘reply’ to message 506, while action 508 provides the userwith the suggested action to “forward” a subset of the plurality ofmessages 501. In one embodiment, the subset of plurality of messages 501associated with the action 508 may be rank ordered for the given action508. While a rank order value is not displayed in screen 500, in otherembodiments, such values may be displayed. Thus, screen 500 is notconstrued as limiting other embodiments. Further, as illustrated,message 507 shows that messages may have a plurality of actions 504.Again, in one embodiment, the plurality of actions 504 may be rankordered for the message 507, and then displayed in such rank orderingfor message 507. Similarly, the rank ordered actions 504 may be includedin rank ordering message 507 along with similar actions, such as action508. In one embodiment, selection of actions 502 icon may enable theuser to selectively display subsets of actions. Thus, in one embodiment,the actions 502 icon may enable the user to display messages having theaction to ‘reply,’ while hiding messages having the action to ‘forward,’or the like. Similarly, selection of a particular message's icon, suchas action 503 icon, automatically opens the associated message 506 in aconfiguration ready for the user to reply to the message, includingproviding appropriate recipients, signature blocks, or the like.Moreover, selection of a particular displayed action and selection of arelated icon may enable the user to take a global action over the subsetof labeled messages. Thus, selection of a forward action 502 mightenable each of messages associated with the action 508 to forward, mightconfigure each of the messages ready for forwarding. In one embodiment,a candidate set of recipients for the forwarded messages may beautomatically provided to the user based on historical actions by theuser, as further determined by one or more classifiers, or the like.

As noted above, predicting how a user might respond to a given messageprovides an opportunity to advertisers, and/or other entities to be ableto improve and focus messages to those users that are more likely to actupon those messages. Thus, predicting, for example, that a user islikely to place orders, and/or otherwise reply to a particular type ofmessage, such as an advertisement, an educational bulletin, medicalbrochure, or the like, provides for more directed mailings. Similarly,predicting which users are more likely to forward messages, acting likegossipers, sneezers, or the like, provides for more directed andefficient mailings.

The above specification, examples, and data provide a completedescription of the manufacture and use of the composition of theinvention. Since many embodiments of the invention can be made withoutdeparting from the spirit and scope of the invention, the inventionresides in the claims hereinafter appended.

1-20. (canceled)
 21. A method comprising: receiving, at a computingdevice, a message in an inbox of a user, said message sent from a senderand comprising content; analyzing the message via the computing device,and based on said analysis, determining a feature vector, said featurevector representing said content of said message; determining, via thecomputing device, a type of said message based on said feature vector;applying, via the computing device, a classifier to said message, saidclassifier being specific to said type of message; determining, via thecomputing device, a set of actions based on said application of theclassifier, each action being a predicted action said classifieridentifies as a future action said user will take on said message; andcausing display, via the computing device, in association with saidinbox, of an interface object in association with said message, saidinterface object enabling selection of said set of actions.
 22. Themethod of claim 21, further comprising: generating an interface objectfor each action in the set of actions; and causing display of eachinterface object within the inbox in association with the message. 23.The method of claim 21, wherein said classifier is a vertical classifierthat accounts for activities the user has taken on other messages ofsaid type.
 24. The method of claim 23, further comprising: determiningthat the user is not a new user, and has not received messages from thesender previously, and employing based on the determination, saidvertical classifier.
 25. The method of claim 21, wherein said classifieris a horizontal classifier that accounts for activities other users havetaken on other messages of said type.
 26. The method of claim 25,further comprising: determining whether the user is a new user, and ifthat is true, then employing said horizontal classifier.
 27. The methodof claim 21, wherein said classifier is a vertical pair-wise classifierthat accounts for activities the user has taken on other messages fromsaid sender.
 28. The method of claim 27, further comprising: determiningwhether the user has received messages from said sender previously, andif that is true, then employing said vertical pair-wise classifier. 29.The method of claim 21, wherein each action in said set of actions isweighted based on a level of confidence determined by said classifier.30. The method of claim 21, wherein at least one of the actions in theset of actions is directed towards preserving a conversation associatedwith the message.
 31. A non-transitory computer-readable storage mediumtangibly encoded with computer-executable instructions, that whenexecuted by a computing device, perform a method comprising: receiving,at the computing device, a message in an inbox of a user, said messagesent from a sender and comprising content; analyzing the message via thecomputing device, and based on said analysis, determining a featurevector, said feature vector representing said content of said message;determining, via the computing device, a type of said message based onsaid feature vector; applying, via the computing device, a classifier tosaid message, said classifier being specific to said type of message;determining, via the computing device, a set of actions based on saidapplication of the classifier, each action being a predicted action saidclassifier identifies as a future action said user will take on saidmessage; and causing display, via the computing device, in associationwith said inbox, of an interface object in association with saidmessage, said interface object enabling selection of said set ofactions.
 32. The non-transitory computer-readable storage medium ofclaim 31, further comprising: generating an interface object for eachaction in the set of actions; and causing display of each interfaceobject within the inbox in association with the message
 33. Thenon-transitory computer-readable storage medium of claim 31, whereinsaid classifier is a vertical classifier that accounts for activitiesthe user has taken on other messages of said type.
 34. Thenon-transitory computer-readable storage medium of claim 33, furthercomprising: determining that the user is not a new user, and has notreceived messages from the sender previously, and employing based on thedetermination, said vertical classifier.
 35. The non-transitorycomputer-readable storage medium of claim 31, wherein said classifier isa horizontal classifier that accounts for activities other users havetaken on other messages of said type.
 36. The non-transitorycomputer-readable storage medium of claim 35, further comprising:determining whether the user is a new user, and if that is true, thenemploying said horizontal classifier.
 37. The non-transitorycomputer-readable storage medium of claim 31, wherein said classifier isa vertical pair-wise classifier that accounts for activities the userhas taken on other messages from said sender.
 38. The non-transitorycomputer-readable storage medium of claim 37, further comprising:determining whether the user has received messages from said senderpreviously, and if that is true, then employing said vertical pair-wiseclassifier.
 39. The non-transitory computer-readable storage medium ofclaim 31, wherein each action in said set of actions is weighted basedon a level of confidence determined by said classifier.
 40. A computingdevice comprising: a processor; and a non-transitory computer-readablestorage medium for tangibly storing thereon program logic for executionby the processor, the program logic comprising: logic executed by theprocessor for receiving, at the computing device, a message in an inboxof a user, said message sent from a sender and comprising content; logicexecuted by the processor for analyzing the message via the computingdevice, and based on said analysis, determining a feature vector, saidfeature vector representing said content of said message; logic executedby the processor for determining, via the computing device, a type ofsaid message based on said feature vector; logic executed by theprocessor for applying, via the computing device, a classifier to saidmessage, said classifier being specific to said type of message; logicexecuted by the processor for determining, via the computing device, aset of actions based on said application of the classifier, each actionbeing a predicted action said classifier identifies as a future actionsaid user will take on said message; and logic executed by the processorfor causing display, via the computing device, in association with saidinbox, of an interface object in association with said message, saidinterface object enabling selection of said set of actions.